Accurate identification of hydrodynamic derivatives is essential for control and navigation of Unmanned Surface Vehicles (USVs), but high-fidelity manoeuvring data from physical sea trials are constrained by cost and safety. Turning Circle (TC) and Zig-Zag (ZZ) trials remain fundamental to IMO and ITTC assessment procedures. This paper extends the Marine Robotics Unity Simulator (MARUS) by introducing a standardised Virtual Sea Trial framework for automated execution and data generation of TC/ZZ manoeuvres, with traceable command-actuation logging, system-identification (SI)-focused data conditioning, and automated extraction of IMO/ITTC-aligned manoeuvring metrics. A key contribution is a dedicated TC/ZZ data acquisition and post-processing pipeline, improving the repeatability and auditability of simulator-based manoeuvres while producing SI-ready datasets for hydrodynamic-derivative identification and digital-twin workflows. Another feature is explicit command-execution separation for differential-thrust steering, where inputs are recorded as ordered rudder-equivalent commands and realised actuation is logged as an execution-level proxy derived from applied thrust. Case-study results demonstrate repeatable and compliant manoeuvre behaviour. For TC tests, the normalised advance differs by approximately 3.9 percent between port and starboard sides, while the tactical diameter differs by approximately 4.6 to 4.7 percent. For ZZ tests, first and second overshoot excesses remain below 1 degree for both +/- 10 degree and +/- 20 degree manoeuvres, satisfying IMO criteria, while peak yaw rates range from approximately 4.1 to 5.8 deg/s. Overall, the framework provides a repeatable and auditable virtual sea-trial workflow for generating IMO/ITTC-aligned datasets and supporting system identification, hydrodynamic-derivative estimation, and digital-twin calibration.

翻译：无人水面艇水动力导数的精确识别对其控制与导航至关重要，但物理海上试验的高保真操纵数据受成本和安全限制。回转试验与Z形试验仍是国际海事组织和国际拖曳水池会议评估程序的核心。本文通过引入标准化虚拟海上试验框架扩展了海洋机器人Unity仿真器，该框架支持回转/Z形操纵的自动化执行与数据生成，具备可追溯指令-驱动记录、面向系统辨识的数据调理及符合国际海事组织/国际拖曳水池会议标准的操纵性指标自动提取功能。核心贡献在于建立了专用的回转/Z形数据采集与后处理流程，在提升基于仿真器的操纵重复性与可审计性的同时，生成适用于水动力导数辨识和数字孪生流程的系统辨识就绪数据集。另一特色在于差分推力转向的显式指令-执行分离机制：输入记录为有序等效舵令，实际驱动以基于施加推力的执行层代理形式记录。案例研究结果表明了可重复且合规的操纵行为：回转试验中，左右舷侧标准化进距偏差约3.9%，战术直径偏差约4.6%~4.7%；Z形试验中，±10°和±20°操纵的首摇角超调量均低于1°，满足国际海事组织标准，峰值转首角速度介于约4.1~5.8度/秒。整体而言，该框架为生成符合国际海事组织/国际拖曳水池会议标准的数据集、支持系统辨识、水动力导数估计及数字孪生校准提供了可重复且可审计的虚拟海上试验工作流程。